Delineating functional and molecular impact of ex vivo sample handling in precision medicine

Consistent handling of samples is crucial for achieving reproducible molecular and functional testing results in translational research. Here, we used 229 acute myeloid leukemia (AML) patient samples to assess the impact of sample handling on high-throughput functional drug testing, mass spectrometry-based proteomics, and flow cytometry. Our data revealed novel and previously described changes in cell phenotype and drug response dependent on sample biobanking. Specifically, myeloid cells with a CD117 (c-KIT) positive phenotype decreased after biobanking, potentially distorting cell population representations and affecting drugs targeting these cells. Additionally, highly granular AML cell numbers decreased after freezing. Secondly, protein expression levels, as well as sensitivity to drugs targeting cell proliferation, metabolism, tyrosine kinases (e.g., JAK, KIT, FLT3), and BH3 mimetics were notably affected by biobanking. Moreover, drug response profiles of paired fresh and frozen samples showed that freezing samples can lead to systematic errors in drug sensitivity scores. While a high correlation between fresh and frozen for the entire drug library was observed, freezing cells had a considerable impact at an individual level, which could influence outcomes in translational studies. Our study highlights conditions where standardization is needed to improve reproducibility, and where validation of data generated from biobanked cohorts may be particularly important.

FBXL12 degrades FANCD2 to regulate replication recovery and promote cancer cell survival under conditions of replication stress

Fanconi anemia (FA) signaling, a key genomic maintenance pathway, is activated in response to replication stress. Here, we report that phosphorylation of the pivotal pathway protein FANCD2 by CHK1 triggers its FBXL12-dependent proteasomal degradation, facilitating FANCD2 clearance at stalled replication forks. This promotes efficient DNA replication under conditions of CYCLIN E- and drug-induced replication stress. Reconstituting FANCD2-deficient fibroblasts with phosphodegron mutants failed to re-establish fork progression. In the absence of FBXL12, FANCD2 becomes trapped on chromatin, leading to replication stress and excessive DNA damage. In human cancers, FBXL12, CYCLIN E, and FA signaling are positively correlated, and FBXL12 upregulation is linked to reduced survival in patients with high CYCLIN E-expressing breast tumors. Finally, depletion of FBXL12 exacerbated oncogene-induced replication stress and sensitized cancer cells to drug-induced replication stress by WEE1 inhibition. Collectively, our results indicate that FBXL12 constitutes a vulnerability and a potential therapeutic target in CYCLIN E-overexpressing cancers.

Prediction model for drug response of acute myeloid leukemia patients

Despite some encouraging successes, predicting the therapy response of acute myeloid leukemia (AML) patients remains highly challenging due to tumor heterogeneity. Here we aim to develop and validate MDREAM, a robust ensemble-based prediction model for drug response in AML based on an integration of omics data, including mutations and gene expression, and large-scale drug testing. Briefly, MDREAM is first trained in the BeatAML cohort (n = 278), and then validated in the BeatAML (n = 183) and two external cohorts, including a Swedish AML cohort (n = 45) and a relapsed/refractory acute leukemia cohort (n = 12). The final prediction is based on 122 ensemble models, each corresponding to a drug. A confidence score metric is used to convey the uncertainty of predictions; among predictions with a confidence score >0.75, the validated proportion of good responders is 77%. The Spearman correlations between the predicted and the observed drug response are 0.68 (95% CI: [0.64, 0.68]) in the BeatAML validation set, -0.49 (95% CI: [-0.53, -0.44]) in the Swedish cohort and 0.59 (95% CI: [0.51, 0.67]) in the relapsed/refractory cohort. A web-based implementation of MDREAM is publicly available at https://www.meb.ki.se/shiny/truvu/MDREAM/ .

SubCellBarCode: integrated workflow for robust spatial proteomics by mass spectrometry

The molecular functions of a protein are defined by its inherent properties in relation to its environment and interaction network. Within a cell, this environment and network are defined by the subcellular location of the protein. Consequently, it is crucial to know the localization of a protein to fully understand its functions. Recently, we have developed a mass spectrometry- (MS) and bioinformatics-based pipeline to generate a proteome-wide resource for protein subcellular localization across multiple human cancer cell lines ( www.subcellbarcode.org ). Here, we present a detailed wet-lab protocol spanning from subcellular fractionation to MS-sample preparation and analysis. A key feature of this protocol is that it includes all generated cell fractions without discarding any material during the fractionation process. We also describe the subsequent quantitative MS-data analysis, machine learning-based classification, differential localization analysis and visualization of the output. For broad applicability, we evaluated the pipeline by using MS data generated by two different peptide pre-fractionation approaches, namely high-resolution isoelectric focusing and high-pH reverse-phase fractionation, as well as direct analysis without pre-fractionation by using long-gradient liquid chromatography-MS. Moreover, an R package covering the dry-lab part of the method was developed and made available through Bioconductor. The method is straightforward and robust, and the entire protocol, from cell harvest to classification output, can be performed within 1-2 weeks. The protocol enables accurate classification of proteins to 15 compartments and 4 neighborhoods, visualization of the output data and differential localization analysis including treatment-induced protein relocalization, condition-dependent localization or cell type-specific localization. The SubCellBarCode package is freely available at https://bioconductor.org/packages/devel/bioc/html/SubCellBarCode.html .

Proteogenomics of non-small cell lung cancer reveals molecular subtypes associated with specific therapeutic targets and immune evasion mechanisms

Despite major advancements in lung cancer treatment, long-term survival is still rare, and a deeper understanding of molecular phenotypes would allow the identification of specific cancer dependencies and immune evasion mechanisms. Here we performed in-depth mass spectrometry (MS)-based proteogenomic analysis of 141 tumors representing all major histologies of non-small cell lung cancer (NSCLC). We identified six distinct proteome subtypes with striking differences in immune cell composition and subtype-specific expression of immune checkpoints. Unexpectedly, high neoantigen burden was linked to global hypomethylation and complex neoantigens mapped to genomic regions, such as endogenous retroviral elements and introns, in immune-cold subtypes. Further, we linked immune evasion with LAG3 via STK11 mutation-dependent HNF1A activation and FGL1 expression. Finally, we develop a data-independent acquisition MS-based NSCLC subtype classification method, validate it in an independent cohort of 208 NSCLC cases and demonstrate its clinical utility by analyzing an additional cohort of 84 late-stage NSCLC biopsy samples.

Molecular evaluation of five different isolation methods for extracellular vesicles reveals different clinical applicability and subcellular origin

Extracellular vesicles (EVs) are increasingly tested as therapeutic vehicles and biomarkers, but still EV subtypes are not fully characterised. To isolate EVs with few co-isolated entities, a combination of methods is needed. However, this is time-consuming and requires large sample volumes, often not feasible in most clinical studies or in studies where small sample volumes are available. Therefore, we compared EVs rendered by five commonly used methods based on different principles from conditioned cell medium and 250 μl or 3 ml plasma, that is, precipitation (ExoQuick ULTRA), membrane affinity (exoEasy Maxi Kit), size-exclusion chromatography (qEVoriginal), iodixanol gradient (OptiPrep), and phosphatidylserine affinity (MagCapture). EVs were characterised by electron microscopy, Nanoparticle Tracking Analysis, Bioanalyzer, flow cytometry, and LC-MS/MS. The different methods yielded samples of different morphology, particle size, and proteomic profile. For the conditioned medium, Izon 35 isolated the highest number of EV proteins followed by exoEasy, which also isolated fewer non-EV proteins. For the plasma samples, exoEasy isolated a high number of EV proteins and few non-EV proteins, while Izon 70 isolated the most EV proteins. We conclude that no method is perfect for all studies, rather, different methods are suited depending on sample type and interest in EV subtype, in addition to sample volume and budget.

The transcriptome-wide landscape of molecular subtype-specific mRNA expression profiles in acute myeloid leukemia

Molecular classification of acute myeloid leukemia (AML) aids prognostic stratification and clinical management. Our aim in this study is to identify transcriptome-wide mRNAs that are specific to each of the molecular subtypes of AML. We analyzed RNA-sequencing data of 955 AML samples from three cohorts, including the BeatAML project, the Cancer Genome Atlas, and a cohort of Swedish patients to provide a comprehensive transcriptome-wide view of subtype-specific mRNA expression. We identified 729 subtype-specific mRNAs, discovered in the BeatAML project and validated in the other two cohorts. Using unique proteomics data, we also validated the presence of subtype-specific mRNAs at the protein level, yielding a rich collection of potential protein-based biomarkers for the AML community. To enable the exploration of subtype-specific mRNA expression by the broader scientific community, we provide an interactive resource to the public.

DEqMS: A Method for Accurate Variance Estimation in Differential Protein Expression Analysis

Quantitative proteomics by mass spectrometry is widely used in biomarker research and basic biology research for investigation of phenotype level cellular events. Despite the wide application, the methodology for statistical analysis of differentially expressed proteins has not been unified. Various methods such as t test, linear model and mixed effect models are used to define changes in proteomics experiments. However, none of these methods consider the specific structure of MS-data. Choices between methods, often originally developed for other types of data, are based on compromises between features such as statistical power, general applicability and user friendliness. Furthermore, whether to include proteins identified with one peptide in statistical analysis of differential protein expression varies between studies. Here we present DEqMS, a robust statistical method developed specifically for differential protein expression analysis in mass spectrometry data. In all data sets investigated there is a clear dependence of variance on the number of PSMs or peptides used for protein quantification. DEqMS takes this feature into account when assessing differential protein expression. This allows for a more accurate data-dependent estimation of protein variance and inclusion of single peptide identifications without increasing false discoveries. The method was tested in several data sets including E. coli proteome spike-in data, using both label-free and TMT-labeled quantification. Compared with previous statistical methods used in quantitative proteomics, DEqMS showed consistently better accuracy in detecting altered protein levels compared with other statistical methods in both label-free and labeled quantitative proteomics data. DEqMS is available as an R package in Bioconductor.

Immediate Adaptation Analysis Implicates BCL6 as an EGFR-TKI Combination Therapy Target in NSCLC

Drug resistance is a major obstacle to curative cancer therapies, and increased understanding of the molecular events contributing to resistance would enable better prediction of therapy response, as well as contribute to new targets for combination therapy. Here we have analyzed the early molecular response to epidermal growth factor receptor (EGFR) inhibition using RNA sequencing data covering 13,486 genes and mass spectrometry data covering 10,138 proteins. This analysis revealed a massive response to EGFR inhibition already within the first 24 h, including significant regulation of hundreds of genes known to control downstream signaling, such as transcription factors, kinases, phosphatases and ubiquitin E3-ligases. Importantly, this response included upregulation of key genes in multiple oncogenic signaling pathways that promote proliferation and survival, such as ERBB3, FGFR2, JAK3, and BCL6, indicating an early adaptive response to EGFR inhibition. Using a library of more than 500 approved and experimental compounds in a combination therapy screen, we could show that several kinase inhibitors with targets including JAK3 and FGFR2 increased the response to EGFR inhibitors. Further, we investigated the functional impact of BCL6 upregulation in response to EGFR inhibition using siRNA-based silencing of BCL6. Proteomics profiling revealed that BCL6 inhibited transcription of multiple target genes including p53, resulting in reduced apoptosis which implicates BCL6 upregulation as a new EGFR inhibitor treatment escape mechanism. Finally, we demonstrate that combined treatment targeting both EGFR and BCL6 act synergistically in killing lung cancer cells. In conclusion, or data indicates that multiple different adaptive mechanisms may act in concert to blunt the cellular impact of EGFR inhibition, and we suggest BCL6 as a potential target for EGFR inhibitor-based combination therapy.

The Proteome of the Dentate Terminal Zone of the Perforant Path Indicates Presynaptic Impairment in Alzheimer Disease

Synaptic dysfunction is an early pathogenic event in Alzheimer disease (AD) that contributes to network disturbances and cognitive decline. Some synapses are more vulnerable than others, including the synapses of the perforant path, which provides the main excitatory input to the hippocampus. To elucidate the molecular mechanisms underlying the dysfunction of these synapses, we performed an explorative proteomic study of the dentate terminal zone of the perforant path. The outer two-thirds of the molecular layer of the dentate gyrus, where the perforant path synapses are located, was microdissected from five subjects with AD and five controls. The microdissected tissues were dissolved and digested by trypsin. Peptides from each sample were labeled with different isobaric tags, pooled together and pre-fractionated into 72 fractions by high-resolution isoelectric focusing. Each fraction was then analyzed by liquid chromatography-mass spectrometry. We quantified the relative expression levels of 7322 proteins, whereof 724 showed significantly altered levels in AD. Our comprehensive data analysis using enrichment and pathway analyses strongly indicated that presynaptic signaling, such as exocytosis and synaptic vesicle cycle processes, is severely disturbed in this area in AD, whereas postsynaptic proteins remained unchanged. Among the significantly altered proteins, we selected three of the most downregulated synaptic proteins; complexin-1, complexin-2 and synaptogyrin-1, for further validation, using a new cohort consisting of six AD and eight control cases. Semi-quantitative analysis of immunohistochemical staining confirmed decreased levels of complexin-1, complexin-2 and synaptogyrin-1 in the outer two-thirds of the molecular layer of the dentate gyrus in AD. Our in-depth proteomic analysis provides extensive knowledge on the potential molecular mechanism underlying synaptic dysfunction related to AD and supports that presynaptic alterations are more important than postsynaptic changes in early stages of the disease. The specific synaptic proteins identified could potentially be targeted to halt synaptic dysfunction in AD.

Tartrate-resistant acid phosphatase (TRAP/ACP5) promotes metastasis-related properties via TGFβ2/TβR and CD44 in MDA-MB-231 breast cancer cells

BACKGROUND

Tartrate-resistant acid phosphatase (TRAP/ACP5), a metalloenzyme that is characteristic for its expression in activated osteoclasts and in macrophages, has recently gained considerable focus as a driver of metastasis and was associated with clinically relevant parameters of cancer progression and cancer aggressiveness.

METHODS

MDA-MB-231 breast cancer cells with different TRAP expression levels (overexpression and knockdown) were generated and characterized for protein expression and activity levels. Functional cell experiments, such as proliferation, migration and invasion assays were performed as well as global phosphoproteomic and proteomic analysis was conducted to connect molecular perturbations to the phenotypic changes.

RESULTS

We identified an association between metastasis-related properties of TRAP-overexpressing MDA-MB-231 breast cancer cells and a TRAP-dependent regulation of Transforming growth factor (TGFβ) pathway proteins and Cluster of differentiation 44 (CD44). Overexpression of TRAP increased anchorage-independent and anchorage-dependent cell growth and proliferation, induced a more elongated cellular morphology and promoted cell migration and invasion. Migration was increased in the presence of the extracellular matrix (ECM) proteins osteopontin and fibronectin and the basement membrane proteins collagen IV and laminin I. TRAP-induced properties were reverted upon shRNA-mediated knockdown of TRAP or treatment with the small molecule TRAP inhibitor 5-PNA. Global phosphoproteomics and proteomics analyses identified possible substrates of TRAP phosphatase activity or signaling intermediates and outlined a TRAP-dependent regulation of proteins involved in cell adhesion and ECM organization. Upregulation of TGFβ isoform 2 (TGFβ2), TGFβ receptor type 1 (TβR1) and Mothers against decapentaplegic homolog 2 (SMAD2), as well as increased intracellular phosphorylation of CD44 were identified upon TRAP perturbation. Functional antibody-mediated blocking and chemical inhibition demonstrated that TRAP-dependent migration and proliferation is regulated via TGFβ2/TβR, whereas proliferation beyond basal levels is regulated through CD44.

CONCLUSION

Altogether, TRAP promotes metastasis-related cell properties in MDA-MB-231 breast cancer cells via TGFβ2/TβR and CD44, thereby identifying a potential signaling mechanism associated to TRAP action in breast cancer cells.

Isoelectric point-based fractionation by HiRIEF coupled to LC-MS allows for in-depth quantitative analysis of the phosphoproteome

Protein phosphorylation is involved in the regulation of most eukaryotic cells functions and mass spectrometry-based analysis has made major contributions to our understanding of this regulation. However, low abundance of phosphorylated species presents a major challenge in achieving comprehensive phosphoproteome coverage and robust quantification. In this study, we developed a workflow employing titanium dioxide phospho-enrichment coupled with isobaric labeling by Tandem Mass Tags (TMT) and high-resolution isoelectric focusing (HiRIEF) fractionation to perform in-depth quantitative phosphoproteomics starting with a low sample quantity. To benchmark the workflow, we analyzed HeLa cells upon pervanadate treatment or cell cycle arrest in mitosis. Analyzing 300 µg of peptides per sample, we identified 22,712 phosphorylation sites, of which 19,075 were localized with high confidence and 1,203 are phosphorylated tyrosine residues, representing 6.3% of all detected phospho-sites. HiRIEF fractions with the most acidic isoelectric points are enriched in multiply phosphorylated peptides, which represent 18% of all the phospho-peptides detected in the pH range 2.5–3.7. Cross-referencing with the PhosphoSitePlus database reveals 1,264 phosphorylation sites that have not been previously reported and kinase association analysis suggests that a subset of these may be functional during the mitotic phase.

Abstract 1109: AAGUGC-microRNAs are an integral part of an oncogenic signaling network driving non-small cell lung cancer proliferation

microRNA dysregulation is a common feature of cancer cells, but the complex roles of microRNAs in cancer are not fully elucidated. Here we used functional genomics to identify oncogenic microRNAs in non-small cell lung cancer (NSCLC) and to evaluate their impact on response to EGFR targeting therapy. Our data demonstrates that microRNAs with an AAGUGC-motif in their seed-sequence increase both cancer cell proliferation and sensitivity to EGFR inhibitors.

Using miR-372 as a prototypic AAGUGC-miRNA we set out to identify target mRNAs and an explanation to the discovered phenotype. Global transcriptomics, proteomics and target prediction, resulted in the identification of more than 500 candidate target mRNAs, including several tumor suppressors involved in the G1/S transition. The clinical relevance of our findings were evaluated by analysis of public domain data of NSCLC patients, revealing that almost 200 of the candidate target mRNAs showed a negative correlation to AAGUGC-miRNAs. In addition, the analysis of NSCLC clinical data supported the link between this microRNA seed-family and cancer cell proliferation and indicated that high expression of this type of microRNAs is associated with shorter relapse free survival.

Expanding the analysis to include additional types of cancer revealed large differences in expression of AAGUGC-miRNA both within and between cancer types. In general the results from the analysis of NSCLC was replicated in other cancer types, where expression of AAGUGC-miRNAs was associated with decreased mRNA levels of tumor suppressor targets and increased expression of genes involved in proliferation.

In conclusion we propose that AAGUGC-microRNAs are an integral part of an oncogenic signaling network, and that these findings have potential therapeutic implications, especially in selecting patients for EGFR-targeting therapy.

Citation Format: Yan Zhou, Oliver Frings, Erik Fredlund, Jorrit Boekel, Rui M. Branca, Lukas M. Orre. AAGUGC-microRNAs are an integral part of an oncogenic signaling network driving non-small cell lung cancer proliferation. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1109.

SpliceVista, a tool for splice variant identification and visualization in shotgun proteomics data

Alternative splicing is a pervasive process in eukaryotic organisms. More than 90% of human genes have alternatively spliced products, and aberrant splicing has been shown to be associated with many diseases. Current methods employed in the detection of splice variants include prediction by clustering of expressed sequence tags, exon microarray, and mRNA sequencing, all methods focusing on RNA-level information. There is a lack of tools for analyzing splice variants at the protein level. Here, we present SpliceVista, a tool for splice variant identification and visualization based on mass spectrometry proteomics data. SpliceVista retrieves gene structure and translated sequences from alternative splicing databases and maps MS-identified peptides to splice variants. The visualization module plots the exon composition of each splice variant and aligns identified peptides with transcript positions. If quantitative mass spectrometry data are used, SpliceVista plots the quantitative patterns for each peptide and provides users with the option to cluster peptides based on their quantitative patterns. SpliceVista can identify splice-variant-specific peptides, providing the possibility for variant-specific analysis. The tool was tested on two experimental datasets (PXD000065 and PXD000134). In A431 cells treated with gefitinib, 2983 splice-variant-specific peptides corresponding to 939 splice variants were identified. Through comparison of splice-variant-centric, protein-centric, and gene-centric quantification, several genes (e.g. EIF4H) were found to have differentially regulated splice variants after gefitinib treatment. The same discrepancy between protein-centric and splice-centric quantification was detected in the other dataset, in which induced pluripotent stem cells were compared with parental fibroblast and human embryotic stem cells. In addition, SpliceVista can be used to visualize novel splice variants inferred from peptide-level evidence. In summary, SpliceVista enables visualization, detection, and differential quantification of protein splice variants that are often missed in current proteomics pipelines.

HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics

We present a liquid chromatography-mass spectrometry (LC-MS)-based method permitting unbiased (gene prediction-independent) genome-wide discovery of protein-coding loci in higher eukaryotes. Using high-resolution isoelectric focusing (HiRIEF) at the peptide level in the 3.7-5.0 pH range and accurate peptide isoelectric point (pI) prediction, we probed the six-reading-frame translation of the human and mouse genomes and identified 98 and 52 previously undiscovered protein-coding loci, respectively. The method also enabled deep proteome coverage, identifying 13,078 human and 10,637 mouse proteins.

Proteomic study of thyroid tumors reveals frequent up-regulation of the Ca2+ -binding protein S100A6 in papillary thyroid carcinoma

BACKGROUND

The accurate diagnosis of thyroid tumors is challenging. Proteomics has emerged as a promising approach for the discovery of molecular diagnostic markers as a potential complement to routine diagnostics.

METHODS

Protein fractions from 29 frozen thyroid tumor tissue samples (10 papillary carcinomas, 9 follicular carcinomas, and 10 follicular adenomas) as well as from normal thyroid tissue were analyzed by surface enhanced laser desorption/ionization time-of-flight mass spectrometry followed by validation by Western blotting and immunohistochemistry.

RESULTS

A Ca2+ binding protein belonging to the S100 family, S100A6, was differentially expressed between papillary and follicular thyroid tumors. Moreover, two posttranslationally modified forms of S100A6 were observed and verified by liquid chromatography-coupled tandem mass spectrometry. Validation by Western blotting displayed a significantly higher expression of S100A6 in papillary thyroid carcinoma (PTC) in comparison with the other tumor groups or normal tissue (p < 0.05). Immunohistochemical analysis on 98 tumors showed that PTC cases had a significantly stronger cytosolic staining and a larger proportion of stained nuclei than follicular tumors. BRAF gene mutation was not significantly associated with S100A6 protein levels.

CONCLUSION

This study supports a role of S100A6 in thyroid tumorigenesis and as a potential aid in the discrimination between follicular thyroid tumors and PTC.

A comparison between protein profiles of B cell subpopulations and mantle cell lymphoma cells

Background

B-cell lymphomas are thought to reflect different stages of B-cell maturation. Based on cytogenetics and molecular markers, mantle cell lymphoma (MCL) is presumed to derive predominantly from naïve, pre-germinal centre (pre-GC) B lymphocytes. The aim of this study was to develop a method to investigate the similarity between MCL cells and different B-cell compartments on a protein expression level.

Methods

Subpopulations of B cells representing the germinal centre (GC), the pre-GC mantle zone and the post-GC marginal zone were isolated from tonsils using automated magnetic cell sorting (AutoMACS) of cells based on their expression of CD27 and IgD. Protein profiling of the B cell subsets, of cell lines representing different lymphomas and of primary MCL samples was performed using top-down proteomics profiling by surface-enhanced laser detection/ionization time-of-flight mass spectrometry (SELDI-TOF-MS).

Results

Quantitative MS data of significant protein peaks (p-value < 0.05) separating the three B-cell subpopulations were generated. Together, hierarchical clustering and principal component analysis (PCA) showed that the primary MCL samples clustered together with the pre- and post-GC subpopulations. Both primary MCL cells and MCL cell lines were clearly separated from the B cells representing the GC compartment.

Conclusion

AutoMACS sorting generates sufficient purity to enable a comparison between protein profiles of B cell subpopulations and malignant B lymphocytes applying SELDI-TOF-MS. Further validation with an increased number of patient samples and identification of differentially expressed proteins would enable a search for possible treatment targets that are expressed during the early development of MCL.

Quantitative membrane proteomics applying narrow range peptide isoelectric focusing for studies of small cell lung cancer resistance mechanisms

Drug resistance is often associated with upregulation of membrane-associated drug-efflux systems, and thus global membrane proteomics methods are valuable tools in the search for novel components of drug resistance phenotypes. Herein we have compared the microsomal proteome from the lung cancer cell line H69 and its isogenic Doxorubicin-resistant subcell line H69AR. The method used includes microsome preparation, iTRAQ labeling followed by narrow range peptide IEF in an immobilized pH-gradient (IPG-IEF) and LC-MS/MS analysis. We demonstrate that the microsomal preparation and iTRAQ labeling is reproducible regarding protein content and composition. The rationale using narrow range peptide IPG-IEF separation is demonstrated by its ability to: (i) lowering the complexity of the sample by two-thirds while keeping high proteome coverage (96%), (ii) providing high separation efficiency, and (iii) allowing for peptide validation and possibly identifications of post-transcriptional modifications. After analyzing one-fifth of the IEF fractions (effective pH range of 4.0-4.5), a total of 3704 proteins were identified, among which 527 were predicted to be membrane proteins. One of the proteins found to be differentially expressed was Serca 2, a calcium pump located in the ER membrane that potentially could result in changes of apoptotic response toward Doxorubicin.

Tumor expression of S100A6 correlates with survival of patients with stage I non-small-cell lung cancer

BACKGROUND

In a previously published in vitro study based on top-down proteomics we found that the calcium-binding proteins S100A6 and S100A4 were affected by exposure to ionizing radiation in a p53-dependent fashion. Both proteins showed post-translational modification changes, and S100A6 also showed increased expression and translocation in response to irradiation. Aim of the present study was to evaluate the expression of S100A6 and S100A4 in non-small-cell lung cancer (NSCLC).

METHODS

S100A6 expression on archival tumor cell lysates from 39 patients with radically resected NSCLC was assessed with SELDI-TOF-MS. S100A6 identity was confirmed using a SELDI-based antibody-capture method on lysates from the A549 lung cancer cell line, cell lysates from two freshly prepared NSCLC samples, four plasma samples and one pleural effusion sample. Immunostainings for S100A6, S100A4 and p53 were performed on tissue microarrays containing 103 stage I surgically resected NSCLC cases and 14 normal lung parenchyma specimens.

RESULTS

The presence of post-translationally modified S100A6 forms was confirmed with SELDI-MS on enriched tumor cell lysates, as well as in plasma and pleural effusion samples. In addition, high S100A6 peak intensity was associated with longer median survival (35 months vs. 18 months for high and low peak intensity, respectively; p=n.s.). The immunohistochemical analysis showed that 25% of tumors were S100A6 positive. S100A6 expression correlated directly with non-squamous histology (p<0.0001) and S100A4 expression (p=0.005), and inversely with p53 expression (p=0.01). S100A6-positive cases showed a trend of longer survival compared with S100A6-negative cases (p=0.07). This difference became significant when the analysis was restricted to p53-negative cases (n=72). In this subgroup of patients, whose tumors likely exhibit a functional p53, S100A6 was an independent prognostic factor of improved survival at multivariate analysis (HR 0.49, 95% CI 0.27-0.81, p=0.017).

CONCLUSIONS

In this study we have validated on clinical material our previous findings on cell lines in terms of S100A6 expression and post-translational modifications pattern in NSCLC. Moreover, the survival results obtained in p53-negative stage I NSCLC cases support the proposed pro-apoptotic function of S100A6 and suggest the hypothesis of a cross regulation between these two proteins.

Evaluation of three principally different intact protein prefractionation methods for plasma biomarker discovery

The aim of this study was to evaluate three principally different top-down protein prefractionation methods for plasma: high-abundance protein depletion, size fractionation and peptide ligand affinity beads, focusing in particular on compatibility with downstream analysis, reproducibility and analytical depth. Our data clearly demonstrates the benefit of high-abundance protein depletion. However, MS/MS analysis of the proteins eluted from the high-abundance protein depletion column show that more proteins than aimed for are removed and, in addition, that the depletion efficacy varies between the different high-abundance proteins. Although a smaller number of proteins were identified per fraction using the peptide ligand affinity beads, this technique showed to be both robust and versatile. Size fractionation, as performed in this study, focusing on the low molecular weight proteome using a combination of gel filtration chromatography and molecular weight cutoff filters, showed limitations in the molecular weight cutoff precision leading detection of high molecular weight proteins and, in the case of the cutoff filters, high variability. GeLC-MS/MS analysis of the fractionation methods in combination with pathway analysis demonstrates that increased fractionation primarily leads to high proteome coverage of pathways related to biological functions of plasma, such as acute phase reaction, complement cascade and coagulation. Further, the prefractionation methods in this study induces limited effect on the proportion of tissue proteins detected, thereby highlighting the importance of extensive or targeted downstream fractionation.

Up-regulation, modification, and translocation of S100A6 induced by exposure to ionizing radiation revealed by proteomics profiling

The cellular response to genotoxic stress is a complex cascade of events including altered protein expression, interactions, modifications, and relocalization, leading to cell cycle arrest and DNA repair or to apoptosis. p53 protein has a central role in this process, and p53 status is an important factor in the response of a tumor to genotoxic anticancer therapy. We studied p53-related changes postexposure to ionizing radiation using top-down mass spectrometry. Initially two cell lines were compared, HCT116 p53 wild type (wt) and p53(-/-), in a time course study postirradiation. In the p53 wt cell line a striking increase of a 10.2-kDa protein was detected, and this protein was identified with MS/MS analysis as S100A6. Further MS profiling led to detection of two post-translationally modified variants of S100A6, namely glutathionylated and cysteinylated forms. In p53 wt cells, a specific shift from glutathionylated to cysteinylated S100A6 occurred postirradiation. The p53 dependence of this specific change in protein level and modification pattern of S100A6 postirradiation was confirmed in a panel of four lung cancer cell lines (H23, U1810, H69, and A549) with different p53 status and using small interfering RNA against p53. Interestingly the closely related S100 family protein S100A4 showed the same changes in modification pattern post-ionizing radiation in the p53 wt lung cancer cell line, and S100A4 also showed p53-dependent expression. Using confocal microscopy, relocalization of S100A6 from nucleus to cytosol and a colocalization with tropomyosin in stress fibers was detected in A549 cells postirradiation. This relocalization coincided with the change in S100A6 modification pattern. Based on these results, we suggest that S100A6 and S100A4 are regulated via redox modifications in vivo and that these proteins are involved in the cellular response to genotoxic stress.

p53 is involved in clearance of ionizing radiation-induced RAD51 foci in a human colon cancer cell line

We have investigated p53-related differences in cellular response to DNA damaging agents, focusing on p53s effects on RAD51 protein level and sub-cellular localization post exposure to ionizing radiation. In a human colon cancer cell line, HCT116 and its isogenic p53-/- subcell line we show here p53-independent RAD51 foci formation but interestingly the resolution of RAD51 foci showed clear p53 dependence. In p53 wt cells, but not in p53-/- cells, RAD51 protein level decreased 48 h post irradiation and fluorescence immunostaining showed resolution of RAD51 foci and relocalization of RAD51 to nucleoli at time points corresponding to the decrease in RAD51 protein level. Both cell lines rejoined DNA double strand breaks efficiently with similar kinetics and p53 status did not influence sensitivity to DNA damaging agents. We suggest that p53 has a role in RAD51 clearance post DSB repair and that nucleoli might be sites of RAD51 protein degradation.

Rad51-related changes in global gene expression

High expression of Rad51, the catalytic component in homologous recombination, has been reported to contribute to genomic instability. To elucidate biological processes related to Rad51, we performed global gene expression analysis on human fibrosarcoma cells induced to express variable Rad51 levels. The results indicate that Rad51 overexpression mediates late rather than early transcriptional responses. Using Gene Ontology analysis, we extracted functional annotations for Rad51-related changes in gene expression that were independent of general cell culture effects. High Rad51 levels conferred increased expression of genes involved in actin remodelling. These changes were accompanied by alterations in cell morphology. Moreover, core components of the mismatch repair (MMR) machinery were down-regulated in response to increased Rad51 expression. Given the role of MMR in the correction of DNA mismatches during replication and recombination, a concurrent increase in Rad51 levels and decrease in the expression of MMR genes could conceivably act synergistically towards genomic instability.